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used to set ad prices, find new drugs more quickly or fine-tune financial models

R is also the name of a popular programming language used by a growing number of data analysts inside corporations and academia.

Here at Revolution Analytics, we’d like to thank all of the data scientists who participated in our first R in Business competition and congratulate the winners. Each of the applications selected demonstrates how predictive analytics with R goes well beyond traditional business intelligence to empower business decision-makers to evaluate critical success factors within important business processes early and often. We see from the winning entries that a wide variety of industries and processes – from marketing, heavy manufacturing, clinical trial design, and IT project management all share a need for ongoing predictive analysis. Revolution Analytics delivers the only R-based enterprise analytics framework, and by examining undiscovered applications of the R language, Revolution Analytics can further refine R tools to meet all organizations’ deep analysis needs.

Learn more about the winning entries in the slide show below:

Part of what we are doing is helping to consumerize or democratize analytics. Because we can provide this software so much more cost effectively, it's giving opportunities for individuals, startups, small and medium businesses to come in and have equal analytic capability and processing power both from a software standpoint, but also from the more cost-effective hardware that we're able to run on to give them the same tools that these giant organizations do. So now all of a sudden we've started to level the playing field a little bit.

It's incredibly diverse. It ranges from pharmaceuticals for drug developments, biostatistics, gene analysis, genetic analysis into finance. It's very heavily used in hedge funds, quantitative finance risk, credit analysis, fraud detection, understanding customer churn, understanding customer behavior, pricing optimization forecasting. We have customers who are entertainment or gaming companies using it to understand buying patterns and effectiveness of different media campaigns. So it ranges anywhere from life sciences to finance to Internet to telecom.

provides a new framework for fast and efficient multi-core processing of large data sets,

After long use in academia, R only recently began to appear in the business world. Among the vendors bringing R into the commercial realm are SAS, Netezza (NYSE: NZ), Revolution Analytics and IBM (NYSE: IBM), which acquired SPSS.

In just two years, Nie's new company has won blue-chip customers such as Bank of America, Motorola and Pfizer.

Revolution Analytics provides value by taking the most recent release from the R community and adding scalability and other functionality so that R can be implemented and seamlessly work in a commercial environment. Revolution R provides a development environment so that data scientists can write and debug R code more effectively, and web service APIs that integrate with other BI tools and dashboards so that R can work with business intelligence tools and visual discovery tools. In addition, Revolution Analytics makes money through professional and support services.

For example, IBM’s PureData System for Analytics (IBM’s new name for its MPP Netezza appliance) uses the in-database approach with an R instance running on each processing unit in the database, each of which is connected to an R server via ODBC. The analytics are invoked as the data is served up to the processor such that the algorithms run in parallel across all of the data.

With data analysis showing up in domains as varied as baseball, evidence-based medicine, predicting recidivism and child support lapses, judging wine quality, credit scoring, supermarket scanner data analysis, and “genius” recommendation engines, “business analytics” is part of the zeitgeist. This is a good moment for actuaries to remember that their discipline is arguably the first – and a quarter of a millennium old – example of business analytics at work.

This session will include an overview of the R statistical computing environment as well as a sequence of brief case studies of actuarial analyses in R. Case studies will include examples from loss distribution analysis, ratemaking, loss reserving, and predictive modeling.

It's available as an Oracle 11g database option and costs $23,000 per processor license.

It's not surprising that Oracle has moved to support R, which "has become a real ubiquitous force in advanced analytics," said Forrester Research analyst James Kobielus. "It's everywhere. Enterprise adoption of it has been growing steadily. When we ask our customers what they're using for statistical modeling they'll say SAS or [IBM's] SPSS, but they increasingly say R in the same breath."

It's not surprising that Oracle has moved to support R, which "has become a real ubiquitous force in advanced analytics," said Forrester Research analyst James Kobielus. "It's everywhere. Enterprise adoption of it has been growing steadily. When we ask our customers what they're using for statistical modeling they'll say SAS or [IBM's] SPSS, but they increasingly say R in the same breath."

el procesamiento de datos se encuentra en la edad de oro

The R statistical software is the fastest growing analytics platform in the world, and is established in both academia and corporations for robustness, reliability and accuracy.

“R is really important to the point that it’s hard to overvalue

R is particularly useful because it contains a number of built-in mechanisms for organizing data, running calculations on the information and creating graphical representations of data sets

Es el nombre de un proyecto de código abierto consistente en un lenguaje de programación y un software de código abierto. Este software nos permite poder analizar datos de múltiples formas.

Es un software de uso común en departamentos de business intelligence dentro de las empresas, pero también es utilizado en investigación. 

Al tratarse de un software de código abierto, podemos decir que está vivo. La comunidad de R trabaja constantemente en desarrollar nuevas versiones mejoradas y en elaborar paquetes específicos para diferentes tipos de análisis. Así podemos encontrar paquetes de todo tipo (4293 a fecha de hoy), desde específicos para biólogos o genetistas, hasta modelos de hábitos de compra para marketing, pasando evidentemente por paquetes estadísticos de todo tipo y calidad.

The “Comprehensive R Archive Network” (CRAN) is a collection of sites which carry identical material, consisting of the R distribution(s), the contributed extensions, documentation for R, and binaries

he CRAN master site at TU Wien, Austria, can be found at the URL http://cran.R-project.org/ Daily mirrors are available at URLs including